Repository containing other projects.
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Updated
Feb 1, 2021 - Python
Repository containing other projects.
Predict stock market using top news headlines
Given the title of a fake news article A and the title of a coming news article B, program classifies B into agree, disagree, and unrelated.
Leveraging 21,000+ Amazon Reviews to conduct Natural Language Processing (NLP), Sentiment Analysis & Supervised Machine Learning to select the best specialty ice cream flavor for our expansion.
A short django project to preprocess text data for NLP problems.
This repository contains code for preprocessing natural language data for use in NLP applications.
Alexa Sentiment Analysis interprets user emotions from their interactions with Amazon's virtual assistant. By analyzing speech patterns and language, it categorizes sentiments as positive, negative, or neutral. This enhances Alexa's responses, ensuring more personalized and effective interactions.
Sentiment analysis of Steve Jobs speech
Given the title of a fake news article A and the title of a coming news article B, program classifies B into agree, disagree, and unrelated.
Classification of Disaster Tweets as REAL or FAKE using Machine Learning
Sentiment Analysis - Airline Tweets using NLP preprocessing, ML algorithms - Logistic regression, XGboost & Naive bayes
Natural language processing involves the reading and understanding of spoken or written language through the medium of a computer. This includes, for example, the automatic translation of one language into another, but also spoken word recognition, or the automatic answering of questions.
A NLP for summarization, tokenazition of characters, words, & sentences, spell check, removal of tags, numbers, stopwords & punctuation, and topic detection.
This repository contains introductory notebooks for text mining and web scrapping.
Problem Statement: Given the tweets from customers about various tech firms who manufacture and sell mobiles, computers, laptops, etc, the task is to identify if the tweets have a negative sentiment towards such companies or products.
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